Infinite Games customer spotlight

TL;DR: Infinite Games uses Quadratic to run daily product analytics and lightweight “mini-apps” on live Postgres data, replacing tab-hopping and speeding experiment retrospectives. The team has Quadratic open essentially every day—116 of the last 120 days. “Quadratic replaced three different tools and saves me a ton of time every week.” — Anthony Parente, Head of Product

Team & stack: Head of Product + founding engineer. Postgres (read-only), Mixpanel (client-side events), Gemini API, Flux, Quadratic with Python/Plotly.

The challenge

As an early-stage studio, Infinite Games lives and dies by how quickly it can understand player behavior. Mixpanel handled client-side tracking and a few standard charts, but the questions that really mattered like item voting behavior, theme assignments, or where churned players cluster, lived in Postgres.

“I ran into a lot of walls where the data I cared about just wasn’t accessible to me in Mixpanel,” says Anthony Parente, Head of Product. Answering them meant bouncing between terminals, notebooks, APIs, and BI tools, a slow and brittle process that was hard to share or reproduce.

The team needed a way to work directly on live data, go deeper than event dashboards, and keep the analysis close enough to the source that results stayed trustworthy.

Why Quadratic

Quadratic lets the product team work on live Postgres data in a familiar spreadsheet canvas, with AI to draft readable SQL and Python/Plotly chart code they can review and refine. “Quadratic has become my go-to platform for working with our user data,” Anthony explains. “I’m constantly pulling datasets on our user interactions to make better product decisions or test a new hypothesis.”

Queries, code, and grid cells live together, so a change in one place automatically recomputes downstream steps. Every chart can show its underlying logic, which makes results easy to validate and reuse. Instead of rebuilding the same work across tools or waiting in a queue, the team moves from question to chart and shares a link to the exact artifact that produced the answer.

What they built

1. Product analytics beyond Mixpanel.

For Runaway Rivals, a core game mode, Anthony linked directly from a Mixpanel board to a Quadratic sheet that queries Postgres, so anyone starting in events can continue the analysis on live data.

Anthony describes the question, Quadratic drafts human-readable SQL, and the result becomes a chart, often with Plotly code generated from a single prompt. “One shot, one prompt, got exactly what I was looking for,” he says of a complex visualization he wouldn’t have coded from scratch.

Daily helper queries (most-used items, utilization rates, product-health checks) sit next to core metrics and get copied into new sheets as templates when they prove useful.

2. Mini-apps for evals and operations.

The team built lightweight “mini-apps” inside a sheet to collapse multi-tool workflows. One example takes a system prompt and user inputs from the database, calls Gemini, converts JSON responses into a table, forwards results to Flux, and displays the outcome inline.

“It used to take minutes hopping from one tool to another,” Anthony says. “Now it’s sequenced in one place, and updating a single cell triggers the whole flow.”

The same pattern powers fast lookups too. Change a variable to a rare item name and a second query fetches the exact owner on demand, turning the sheet into a useful internal tool without writing a frontend.

3. Deeper visuals, faster iteration.

With Plotly, the team created rich maps to visualize churned versus retained users at sub-state granularity, an analysis that typical BI tools rendered only at coarse state-level detail. “In most other BI tools, you just can’t get maps like this,” Anthony notes. Because charts live beside SQL and data, the team can validate what they’re seeing, prevent double-counting, and iterate quickly when new questions arise.

Results

• Used daily: Quadratic is part of the operating rhythm, open 116 of the last 120 days.
• Faster answers: Product questions move from idea to query to chart in minutes, not multi-tool workflows.
• Explainable outputs: Logic is visible in the sheet, making results easy to validate and reuse.
• Fewer tools: “Quadratic replaced three different tools and saves me a ton of time every week.” — Anthony Parente, Head of Product
• One artifact for many needs: The same sheet supports ad-hoc analysis and recurring checks, keeping the team aligned.
• Closer to users: Staying on live data helps the team ship with more confidence grounded in real behavior.

Anthony’s advice to other early product teams

1. Start with real questions. Point Quadratic at your read-only DB and ask what you actually need to decide.
2. Let AI scaffold. Use prompts to draft SQL and Python, then refine to get exactly what you need.
3. Collapse your toolchain. Pull external APIs, CSVs, PDFs, etc. into the same sheet to remove glue work.
4. Promote scratchpads. Many “throwaway” explorations evolve into production dashboards.